KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
December 2025
David Alvarez-Melis
Senior Researcher
出版物
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scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling
Joel Dapello, Marcel Nassar, Ridvan Eksi, Ban Wang, Jules Gagnon-Marchand, Kenneth Gao, akram Baharlouei, Kyra Thrush, Nina Riehs, Amy Peterson, Aniket Tolpadi, Abhejit Rajagopal, Henry Miller, ashley conard, David Alvarez-Melis, Rory Stark, Simone Bianco, Morgan Levine, Ava P. Amini, Alex Lu, Nicolo Fusi, Ravi Pandya, Valentina Pedoia, Hana El-Samad
NeurIPS 2025 | October 2025
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Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
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A Label is Worth a Thousand Images in Dataset Distillation
Tian Qin, Zhiwei Deng, David Alvarez-Melis
NeurIPS 2024 | June 2024
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Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
ICML 2024 | February 2024
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InfoOT: Information Maximizing Optimal Transport
Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
ICML 2023 | May 2023
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Hierarchical Optimal Transport for Comparing Histopathology Datasets
Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
April 2022
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From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
HCOMP 2021 | September 2021
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Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
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Gradient Flows in Dataset Space
David Alvarez-Melis, Nicolo Fusi
October 2020
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Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
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Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
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Towards Optimal Transport with Global Invariances
AISTATS | April 2019
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Optimal transport in structured domains : algorithms and applications
March 2019
博士論文:Massachusetts Institute of Technology | March 2019
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Towards robust interpretability with self-explaining neural networks
NeurIPS 2018 | December 2018
PDF PDF Publication Publication Publication Publication Publication
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On the Robustness of Interpretability Methods
David Alvarez-Melis, Tommi S. Jaakkola
WHI 2018 | June 2018
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KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
December 2025
-
Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
-
A Label is Worth a Thousand Images in Dataset Distillation
Tian Qin, Zhiwei Deng, David Alvarez-Melis
NeurIPS 2024 | June 2024
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Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
ICML 2024 | February 2024
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InfoOT: Information Maximizing Optimal Transport
Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
ICML 2023 | May 2023
-
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
HCOMP 2021 | September 2021
-
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
-
Gradient Flows in Dataset Space
David Alvarez-Melis, Nicolo Fusi
October 2020
-
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
-
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
-
Towards Optimal Transport with Global Invariances
AISTATS | April 2019
-
Towards robust interpretability with self-explaining neural networks
NeurIPS 2018 | December 2018
PDF PDF Publication Publication Publication Publication Publication
-
On the Robustness of Interpretability Methods
David Alvarez-Melis, Tommi S. Jaakkola
WHI 2018 | June 2018
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-
-
scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling
Joel Dapello, Marcel Nassar, Ridvan Eksi, Ban Wang, Jules Gagnon-Marchand, Kenneth Gao, akram Baharlouei, Kyra Thrush, Nina Riehs, Amy Peterson, Aniket Tolpadi, Abhejit Rajagopal, Henry Miller, ashley conard, David Alvarez-Melis, Rory Stark, Simone Bianco, Morgan Levine, Ava P. Amini, Alex Lu, Nicolo Fusi, Ravi Pandya, Valentina Pedoia, Hana El-Samad
NeurIPS 2025 | October 2025
-
Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
-
Hierarchical Optimal Transport for Comparing Histopathology Datasets
Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
April 2022
-
-
-
Gradient Flows in Dataset Space
David Alvarez-Melis, Nicolo Fusi
October 2020
-
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
-
Optimal transport in structured domains : algorithms and applications
March 2019
博士論文:Massachusetts Institute of Technology | March 2019
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-
-
KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
December 2025
-
Causal integration of chemical structures improves representations of microscopy images for morphological profiling
Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
April 2025
-
Gradient Flows in Dataset Space
David Alvarez-Melis, Nicolo Fusi
October 2020
-
-
-
scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling
Joel Dapello, Marcel Nassar, Ridvan Eksi, Ban Wang, Jules Gagnon-Marchand, Kenneth Gao, akram Baharlouei, Kyra Thrush, Nina Riehs, Amy Peterson, Aniket Tolpadi, Abhejit Rajagopal, Henry Miller, ashley conard, David Alvarez-Melis, Rory Stark, Simone Bianco, Morgan Levine, Ava P. Amini, Alex Lu, Nicolo Fusi, Ravi Pandya, Valentina Pedoia, Hana El-Samad
NeurIPS 2025 | October 2025
-
A Label is Worth a Thousand Images in Dataset Distillation
Tian Qin, Zhiwei Deng, David Alvarez-Melis
NeurIPS 2024 | June 2024
-
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
ICML 2024 | February 2024
-
InfoOT: Information Maximizing Optimal Transport
Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
ICML 2023 | May 2023
-
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
HCOMP 2021 | September 2021
-
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
-
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
-
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
-
Towards Optimal Transport with Global Invariances
AISTATS | April 2019
-
Towards robust interpretability with self-explaining neural networks
NeurIPS 2018 | December 2018
PDF PDF Publication Publication Publication Publication Publication
-
On the Robustness of Interpretability Methods
David Alvarez-Melis, Tommi S. Jaakkola
WHI 2018 | June 2018
-
-
-
Hierarchical Optimal Transport for Comparing Histopathology Datasets
Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
April 2022
-
-
-
Optimal transport in structured domains : algorithms and applications
March 2019
博士論文:Massachusetts Institute of Technology | March 2019
-